基于优先权拍卖的产能分配机制研究

本文考虑一个供应商和两个独立零售商构成的供应链系统。当供应商的产能受到约束时，零售商可能会竞争有限的产能。本文提出将“优先分配权”作为一个有价值的标的物进行拍卖，按照出价高低确定优先分配顺序。本文证明了优先权拍卖机制属于共同价值模型，并提出了两类拍卖机制：事先拍卖和事后拍卖。本文证明两类优先权拍卖机制均会促使零售商提交真实的需求作为订单量，并且满足收益等价定理。而就供应商期望利润而言，事后优先权拍卖机制要高于事先优先权拍卖机制。     

Channel Strategies and Stocking Policies in Uncapacitated and Capacitated Supply Chains*

A supply chain consisting of a single supplier distributing two independent products through multiple retailers is analyzed in this paper. The supplier needs to incentivize its retailers to adopt stocking policies that are mutually advantageous and that result in the optimal level of market coverage. The focus is on determining the optimal stocking policies for retailers and the resulting distribution strategy given that the supplier has either unlimited or limited capacity. The results provide insights on the optimal distribution strategy and stocking policies for the supply chain. In general, the paper shows that it is optimal for the supplier to use an intensive distribution strategy (i.e., the products are stocked by all retailers). Selective or exclusive strategies are optimal only when retailers are risk averse, stocking synergies exist, and there are differences in demand or supply uncertainties across products. The analysis also shows that retailers hold larger stocks of a product which generates higher supplier margins but only when the supplier has unlimited capacity. If the supplier has limited capacity, then their margins have no effect on retailers' stocking decisions. Contrary to conventional wisdom, retailers hold larger stocks of a product that has less demand uncertainty as compared to one that has more demand uncertainty.     

Managing stochastic demand in an Inventory Routing Problem with transportation procurement

We study an Inventory Routing Problem in which the supplier has a limited production capacity and the stochastic demand of the retailers is satisfied with procurement of transportation services. The aim is to minimize the total expected cost over a planning horizon, given by the sum of the inventory cost at the supplier, the inventory cost at the retailers, the penalty cost for stock-out at the retailers and the transportation cost. First, we show that a policy based just on the average demand can have a total expected cost infinitely worse than the one obtained by taking into account the overall probability distribution of the demand in the decision process. Therefore, we introduce a stochastic dynamic programming formulation of the problem that allows us to find an optimal policy in small size instances. Finally, we design and implement a matheuristic approach, integrating a rollout algorithm and an optimal solution of mixed-integer linear programming models, which is able to solve realistic size problem instances. Computational results allow us to provide managerial insights concerning the management of stochastic demand.     

Economic analysis of demand uncertainty and delayed information sharing in a third-party managed supply chain

Designers and retailers in consumer products industry are faced with high demand volatility and potential loss of profit from design piracy. Many retailers rely on third-party supply chain managers (SCMs) to manage global supply chains. A SCM starts raw materials procurement and production process based on expected demand and takes financial risks associated with demand uncertainty. But a retailer often delays sharing product design information with SCM forcing it to expedite production and distribution processes incurring additional financial penalties. To analyse economic impact of delayed information sharing under uncertain demand, we develop a mathematical model. Our model indicates that higher demand volatility lessens the effect of penalty associated with delayed information sharing for retailers. The model also shows that for a given demand volatility, per-unit premium increases asymptotically for a retailer compared to marginal production cost increase for SCM. Such findings are not intuitive for SCMs or retailers.     

Interorganizational Collaborative Forecasting and Replenishment Systems and Supply Chain Implications

Collaborative Forecasting and Replenishment (CFAR) is a new interorganizational system that enables retailers and manufacturers to forecast demand and schedule production jointly. The capabilities of CFAR exceed those of the traditional EDI because CFAR allows exchange of complex decision support models and manufacturer/retailer strategies. The proponents of CFAR claim that the fastest way for retailers and manufacturers to slash inventory costs and product shortages is by coordinating their decisions. The impact of CFAR on the supply chain using a model consisting of a manufacturer selling its product through two independent identical retailers is analyzed. The model assumes that the manufacturer doesn't face capacity constraints, the demand is stationary, and retailer prices are constant over time; the shortages are backordered at the manufacturer and retailers to isolate the effects of information sharing in CFAR. The most significant findings relate to the increase in the cost incurred by the nonparticipant in CFAR, the increase in the manufacturer's cost of serving the nonparticipant if the participant can obtain delivery guarantees in return for demand information sharing, and the incentives of the players to move towards universal retailer participation in CFAR. The findings are explained using the risk structure faced by the players in the supply chain. The managerial implications of the impact of CFAR on the supply chain structure are also discussed.     

区分仓库与货架库存需求影响效应的零售商库存决策

既往有关库存水平影响需求条件下的库存问题研究中,通常对终端库存水平是否存在货架与零售商仓库库存水平的区别未作深入探讨。本文的研究认为,现实中许多零售商拥有仓库,其现有库存水平包括仓库库存和货架库存两部分,而影响需求的仅为与货架展示能力相关的库存,因此有必要对二者的需求影响效应进行区分。在明确这一区别的前提下,本文首先建立了供应商管理库存情况下库存水平影响需求问题的一般库存模型,给出零售商的最优订货策略;并考虑货架的容量限制,给出零售商启用仓库的判断条件。由于仓库库存仅在能够影响货架展示能力的条件下才能够影响消费需求,本文还进一步讨论了在零售商拥有仓库时,区分货架与仓库的库存水平影响需求条件下的最优库存与订货决策。这对于经营不同特征商品的零售商在进行是否需要拥有仓库,以及拥有仓库条件下的库存决策具有很好的参考价值。     

考虑产能约束的模糊供应链网络均衡研究

在考虑制造商存在产能约束情形下,研究由多个相互竞争的制造商与零售商组成且零售商处面临着模糊需求的供应链网络均衡问题。利用模糊事件的可信性理论,推导零售商的模糊期望利润。通过变分不等式,构建具有模糊需求的单商品供应链网络均衡状态。最后,利用对数二次近似预测校正算法,讨论分析制造商产能约束对供应链均衡解的影响。     

Resource Flexibility Issues in Multistage Manufacturing

We test the situational impact of two types of resource flexibility, machine flexibility and labor flexibility, in a material requirements planning (MRP)-driven production system. Machine flexibility has not been treated in prior multistage research, only labor flexibility. Machine flexibility is closely related to a plant's positioning strategy. A process-focused plant opts for considerable machine flexibility by choosing general-purpose equipment. Resource flexibility, if effective, can be an attractive alternative to two other types of buffers, inflated inventories and costly capacity cushions. Our simulation results, using factor settings established earlier by a panel of managers, show that resource flexibility is indeed an effective buffer against uncertainties such as end-item demand variability, capacity bottlenecks, equipment failures, and yield losses. Machine flexibility is especially helpful in environments characterized by high uncertainties, tight capacities, and large lot sizes. Worker flexibility has a similar, but less dramatic, impact. Benefits are most striking with customer service, rather than with inventory or labor productivity. Finally, we show that simultaneous introduction of both machine and labor flexibility yields only marginal improvements over either kind of flexibility alone.     

基于同质设备多台配置的独立生产单元构建决策

单元化生产作为一种较好实现生产柔性与生产效率融合的先进生产方式,在变种变量需求环境下它已被大量生产企业特别是装配式生产企业所采用。生产单元构建问题是单元化生产系统设计的关键问题和首要问题,也是单元化生产研究领域的一个热点。本文研究设备易复制情形下,通过配置多台同质设备来实现生产单元间无物料移动,并保证生产单元间工作量均衡的独立生产单元构建问题。本文在综合考虑换装时间、加工顺序、设备生产能力、产品需求量等多个实际生产要素的基础上,建立了以平均总流程时间和各生产单元总流程时间与平均总流程时间偏差最小为目标的数学模型,并开发了一个启发式算法来求解数学模型,最后通过数值算例验证了模型和算法的有效性。     

需求不确定下生产能力与竞争优势之间的关系

在需求不确定的条件下,用生产能力刻画产量决策的柔性,用古诺模型描述企业间的(产量)竞争,建立一个两企业战略竞争博弈模型,并利用博弈均衡构建柔性水平与竞争优势之间的函数关系。比较静态分析结果表明,(1)其他条件不变,一家企业的相对竞争优势随着自己的生产能力增加而增加,但随着对手的生产能力增加而降低;(2)生产能力较高的企业将获得较高的绝对竞争优势。这些结果暗示,柔性水平与竞争优势之间呈现一种正向的变动关系。这一结论一方面在一定程度上澄清了战略管理文献中呈现出的"战略柔性与竞争优势之间的联系方向模凌两可"这一问题;另一方面,由于引入了竞争性战略互动,从而将基于个人理性决策的结果扩展到战略相互依赖的竞争性情形下。     

A MODEL FOR BATCH ADVANCED AVAILABLE‐TO‐PROMISE

The available‐to‐promise (atp) function is becoming increasingly important in supply chain management since it directly links production resources with customer orders. In this paper, a mixed integer programming (mip) ATP model is presented. This model can provide an order‐promising and ‐fulfillment solution for a batch of orders that arrive within a predefined batching interval. A variety of constraints, such as raw material availability, production capacity, material compatibility, and customer preferences, are considered. Simulation experiments using the model investigate the sensitivity of supply chain performance to changes in certain parameters, such as batching interval size and customer order flexibility.     

OPTIMAL ORDERING IN A DUAL‐SUPPLIER SYSTEM WITH DEMAND FORECAST UPDATES

We study how an updated demand forecast affects a manufacturer's choice in ordering raw materials. With demand forecast updates, we develop a model where raw materials are ordered from two suppliers—one fast but expensive and the other cheap but slow—and further provide an explicit solution to the resulting dynamic optimization problem. Under some mild conditions, we demonstrate that the cost function is convex and twice‐differentiable with respect to order quantity. With this model, we are able to evaluate the benefit of demand information updating which leads to the identification of directions for further improvement. We further demonstrate that the model applies to multiple‐period problems provided that some demand regularity conditions are satisfied. Data collected from a manufacturer support the structure and conclusion of the model. Although the model is described in the context of in‐bound logistics, it can be applied to production and out‐bound logistics decisions as well.     

Cooperative sales promotion with a point-sharing policy: Advantages and limitations

Consumption-point programs have been commonly implemented in retail industries in efforts to promote sales and improve customer loyalty. In Korea, many retailers from different industries use a point-sharing policy to augment the conventional consumption-point program of each retailer. In a multi-retailer coalition under such a cooperative sales promotion policy, by purchasing from one coalition retailer, customers earn points that they can redeem points at other retailers in the coalition. On one hand, the introduction of this policy gives customers great flexibility for redeeming earned points, which can increase the demand at all retailers who promote the policy. On the other hand, the additional product costs associated with the points created by one retailer may spill over and be partly borne by other retailers, possibly distorting the coalition members’ equilibrium decisions under decentralized control. Under the general assumptions about the demand functions, we developed a model consisting of two retailers with fixed retail prices and addressed the retailers’ equilibrium decisions under a pure point-sharing policy. The findings suggest that the policy resulted in a cost spillover phenomenon. Then, we revealed that a pure point-sharing policy may fail to maximize the total profit of the coalition. Moreover, we showed that a pure point-sharing policy does not dominate the individual point scheme, which may explain the reason that point sharing is useful but not ubiquitously used in the real world. Our numerical examples also illustrate the way a pure point-sharing policy influences retailers’ profits when retail prices are decision variables. To improve the overall profit under the point-sharing policy further, we propose a target rebate contract to coordinate a pair of retailers. This contract can maximize the total profit and arbitrarily split the profit between retailers.     

考虑不同经营模式的零售商纵向整合策略选择:前向,后向还是不整合？

随着互联网的发展,"新零售"表现形式之一的纵向整合成为零售商转型升级的重要策略。考虑了产品之间竞争性,分别研究了分销模式、平台模式和混合模式下,零售商采取不进行纵向整合、前向整合和后向整合的利润,通过对比给出零售商最优的纵向整合策略选择条件。最后,分析了不同经营模式对零售商纵向整合策略选择的影响。研究发现：第一,随着潜在需求的增加,在三种经营模式下零售商的最优策略都从不进行纵向整合变为后向整合、前向整合;第二,随着产品之间竞争程度增加,在分销模式和平台模式下,零售商的最优策略从后向整合变为不进行纵向整合、前向整合,在混合模式下,零售商的最优策略从后向整合或不进行纵向整合变为前向整合;第三,随着佣金费率增加,在平台模式下,零售商的最优策略从前向整合变为后向整合、不进行纵向整合,在混合模式下,零售商的最优策略从前向整合或后向整合制造商2变为不进行纵向整合、后向整合制造商1。     

DEMAND MANAGEMENT: THE EVALUATION OF PRICE AND DUE DATE NEGOTIATION STRATEGIES USING SIMULATION

The research considers the problem of demand management in a firm where the firm's historical delivery service level reputation influences the number of quotation requests from its potential customers. Customers have a maximum and the firm has a minimum net price to due date tradeoff curve for each job. The demand management function bargains with the customer over price and promised due date. Bargaining finishes either with an agreed price and delivery date or with the customer refusing the firm's bid and placing the order elsewhere. The firm's objective is to maximize its long-term net revenue. The firm's demand management negotiation strategy guides this bidding process. The research demonstrates the use of simulation to test different demand management bidding and negotiation strategies for different market and firm scenarios. The demonstration uses 16 scenarios to test the different demand management negotiation strategies with a model of a classical job shop in a classical market. The investigation examines finite scheduling-based due date estimation methods, as well as the more traditional parameter-based methods. This demonstration shows that it is possible to test different bidding policies, using a simulation model of a firm and its customers, and to obtain usable results.     

On the benefits of operational flexibility in a distribution network with transshipment

We consider a centralized distribution network with multiple retailers who receive replenishment inventory to satisfy customer demand of the local markets. The operational flexibility of the network is defined as the opportunity that one retailer's excess inventory can be transferred to satisfy other retailers’ unmet customer demand due to stock-outs. A general modeling framework is developed to optimize retailers’ order quantities under any possible flexibility level of a stylized two-stage distribution network. We apply the framework to formulate and solve the transshipment problem of a distribution network with three retailers. Six typical flexibility levels are investigated to make the comparison study on the firm's profit performance under three ordering quantity policies: average demand, newsvendor order quantity, and optimal order quantity. We find that the operational flexibility and system optimization are complements to the firm's performance. The ordering policy with newsvendor ordering quantity can perform fairly well with moderate flexibility level when compared with the optimized ordering policy with full flexibility.     

Retailer Transshipment versus Central Depot Allocation for Supply Network Design

We consider a supply chain structure with shipments from an external warehouse directly to retailers and compare two enhancement options: costly transshipment among retailers after demand has been realized vs. cost‐free allocation to the retailers from the development of a centralized depot. Stochastic programming models are developed for both the transshipment and allocation structures. We study the impact of cost parameters and demand coefficient of variation on both system structures. Our results show an increasing convex relationship between average costs and demand coefficient of variation, and furthermore that this increase is more pronounced for the allocation structure. We employ simulation and nonlinear search techniques to computationally compare the cost performance of allocation and transshipment structures under a wide range of system parameters such as demand uncertainty and correlation; lead times from the external warehouse to retailers, from warehouse to central depot, and from depot to retailers; and transshipment, holding, and penalty costs. The transshipment approach is found to outperform allocation for a broad range of parameter inputs including many situations for which transshipment is not an economically sound decision for a single period. The insights provided enable the manager to choose whether to invest in reducing lead times or demand uncertainty and assist in the selection of investments across identical and nonidentical retailers.     

Managing Downstream Competition via Capacity Allocation

Consider a supply chain with one supplier and multiple retailers. The supplier produces a single product and sells it to the retailers, who in turn sell the product to consumers. The supplier has limited production capacity, and the retailers are engaged in a Cournot competition at the consumer/market level. When the sum of the retailer orders exceeds the capacity, the supplier allocates her capacity according to a pre‐announced allocation mechanism. Two mechanisms are considered: proportional allocation and lexicographic allocation. An extensive study of the two allocation mechanisms shows that the lexicographic mechanism has the ability to dampen the competition at the retail level, increasing the profits for both the supplier and the supply chain.     

The impact of the product mix on the value of flexibility

Product-mix flexibility is one of the major types of manufacturing flexibility, referring to the ability to produce a broad range of products or variants with presumed low changeover costs. The value of such a capability is important to establish for an industrial firm in order to ensure that the flexibility provided will be at the right level and used profitably rather than in excess of market requirements and consequently costly. We use option-pricing theory to analyse the impact of various product-mix issues on the value of flexibility. The real options model we use incorporates multiple products, capacity constraints as well as set-up costs. The issues treated here include the number of products, demand variability, correlation between products, and the relative demand distribution within the product mix. Thus, we are interested in the nature of the input data to analyse its effect on the value of flexibility. We also check the impact at different capacity levels. The results suggest that the value of flexibility (i) increases with an increasing number of products, (ii) decreases with increasing volatility of product demand, (iii) decreases the more positively correlated the demand is, and (iv) reduces for marginal capacity with increasing levels of capacity. Of these, the impact of positively correlated demand seems to be a major issue. However, the joint impact of the number of products and demand correlation showed some non-intuitive results.     

Optimal Dynamic Order Scheduling under Capacity Constraints Given Demand‐Forecast Evolution

We consider a manufacturer without any frozen periods in production schedules so that it can dynamically update the schedules as the demand forecast evolves over time until the realization of actual demand. The manufacturer has a fixed production capacity in each production period, which impacts the time to start production as well as the production schedules. We develop a dynamic optimization model to analyze the optimal production schedules under capacity constraint and demand‐forecast updating. To model the evolution of demand forecasts, we use both additive and multiplicative versions of the martingale model of forecast evolution. We first derive expressions for the optimal base stock levels for a single‐product model. We find that manufacturers located near their market bases can realize most of their potential profits (i.e., profit made when the capacity is unlimited) by building a very limited amount of capacity. For moderate demand uncertainty, we also show that it is almost impossible for manufacturers to compensate for the increase in supply–demand mismatches resulting from long delivery lead times by increasing capacity, making lead‐time reduction a better alternative than capacity expansion. We then extend the model to a multi‐product case and derive expressions for the optimal production quantities for each product given a shared capacity constraint. Using a two‐product model, we show that the manufacturer should utilize its capacity more in earlier periods when the demand for both products is more positively correlated.